Multilevel regression analysis assesses system reliability in industrial machinery fleets, suggesting targeted maintenance improvements.
Industrial machinery fleets in Kenya face challenges related to system reliability due to varying conditions such as operational wear and environmental factors. A multilevel regression model was applied to assess the reliability of industrial machinery fleets, considering both fixed and random effects. The multilevel regression analysis revealed significant differences ($eta = -0.32, p < 0.01$) in system reliability across different geographical regions, indicating a need for targeted interventions. Our findings highlight the importance of regional-specific analyses to improve machinery fleet reliability and suggest that targeted maintenance strategies could enhance performance by up to 20%. Implementing regionally specific maintenance schedules is recommended to address observed disparities in system reliability.
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Kilonzo et al. (2012) studied this question.
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